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55 results for “SNP genotype data”
Data from: A high density SNP chip for genotyping great tit (Parus major) populations and its application to studying the genetic architecture of exploration behaviour
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Data from: Multiplex preamplification PCR and microsatellite validation allows accurate single nucleotide polymorphism (SNP) genotyping of historical fish scales
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Data from: SNP genotyping elucidates the genetic diversity of Magna Graecia grapevine germplasm and its historical origin and dissemination
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Data from: Finding the right coverage: The impact of coverage and sequence quality on SNP genotyping error rates
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Data from: Origins of cattle on Chirikof Island, Alaska, elucidated from genome-wide SNP genotypes
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Data from: Phylogeography and adaptation genetics of stickleback from the Haida Gwaii archipelago revealed using genome-wide SNP genotyping
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Impatiens glandulifera SNP and SilicoDArT genotyping data
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Data from: Characterisation of microsatellite and SNP markers from Miseq and genotyping-by-sequencing data among parapatric Urophora cardui (Tephritidae) populations
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Data from: A new multiplex SNP genotyping assay for detecting hybridization and introgression between the M and S molecular forms of Anopheles gambiae
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Data from: Use of genotyping-by-sequencing data to develop a high-throughput and multi-functional SNP panel for conservation applications in Pacific lamprey
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Data from: More affordable and effective noninvasive SNP genotyping using high-throughput amplicon sequencing
<p>Non-invasive genotyping methods have become key elements of wildlife research over the last two decades, but their widespread adoption is limited by high costs, low success rates, and high error rates. <span>The information lost when genotyping success is low may lead to decreased precision in animal population densities, which could misguide conservation and management actions.</span> <span>Single nucleotide polymorphisms (SNPs) provide a promising alternative to traditionally used microsatellites as SNPs allow amplification of shorter DNA fragments, are less prone to genotyping errors, and produce results that are easily shared among laboratories.</span> Here, we outline a detailed protocol for cost-effective and accurate noninvasive SNP genotyping using multiplexed amplicon sequencing optimized for degraded DNA. <span>We validated this method for individual identification by genotyping 216 scats, 18 hairs and 15 tissues from coyotes (<i>Canis latrans</i>) using 26 SNPs. </span><a name="_Hlk33181599">Our genotyping success rate for scat samples was 93%, and 100% for hair and tissue, representing a substantial increase compared to previous microsatellite-based studies while remaining at a low cost of under $5 per PCR replicate (excluding labor). </a>The accuracy of the genotypes was further corroborated in that genotypes from scats matching known, GPS-collared coyotes were always located within the territory of the known individual. We also show that different levels of multiplexing produced similar results, but that PCR product cleanup strategies can have substantial effects on genotyping success. By making noninvasive genotyping more affordable, accurate, and efficient, this research may allow for a substantial increase in the use of noninvasive methods to monitor and conserve free-ranging wildlife populations.</p>
Data from: Estimations of linkage disequilibrium, effective population size and ROH-based inbreeding coefficients in Spanish Churra sheep using imputed high-density SNP genotypes
In this study, the availability of the Ovine HD SNP BeadChip (HD-chip) and the development of an imputation strategy provided an opportunity to further investigate the extent of linkage disequilibrium (LD) at short distances in the genome of the Spanish Churra dairy sheep breed. A population of 1686 animals, including 16 rams and their half-sib daughters, previously genotyped for the 50K-chip, was imputed to the HD-chip density based on a reference population of 335 individuals. After assessing the imputation accuracy for beagle v4.0 (0.922) and fimpute v2.2 (0.921) using a cross-validation approach, the imputed HD-chip genotypes obtained with beagle were used to update the estimates of LD and effective population size for the studied population. The imputed genotypes were also used to assess the degree of homozygosity by calculating runs of homozygosity and to obtain genomic-based inbreeding coefficients. The updated LD estimations provided evidence that the extent of LD in Churra sheep is even shorter than that reported based on the 50K-chip and is one of the shortest extents compared with other sheep breeds. Through different comparisons we have also assessed the impact of imputation on LD and effective population size estimates. The inbreeding coefficient, considering the total length of the run of homozygosity, showed an average estimate (0.0404) lower than the critical level. Overall, the improved accuracy of the updated LD estimates suggests that the HD-chip, combined with an imputation strategy, offers a powerful tool that will increase the opportunities to identify genuine marker-phenotype associations and to successfully implement genomic selection in Churra sheep.
Data from: Vitis phylogenomics: hybridization intensities from a SNP array outperform genotype calls
Understanding relationships among species is a fundamental goal of evolutionary biology. Single nucleotide polymorphisms (SNPs) identified through next generation sequencing and related technologies enable phylogeny reconstruction by providing unprecedented numbers of characters for analysis. One approach to SNP-based phylogeny reconstruction is to identify SNPs in a subset of individuals, and then to compile SNPs on an array that can be used to genotype additional samples at hundreds or thousands of sites simultaneously. Although powerful and efficient, this method is subject to ascertainment bias because applying variation discovered in a representative subset to a larger sample favors identification of SNPs with high minor allele frequencies and introduces bias against rare alleles. Here, we demonstrate that the use of hybridization intensity data, rather than genotype calls, reduces the effects of ascertainment bias. Whereas traditional SNP calls assess known variants based on diversity housed in the discovery panel, hybridization intensity data survey variation in the broader sample pool, regardless of whether those variants are present in the initial SNP discovery process. We apply SNP genotype and hybridization intensity data derived from the Vitis9kSNP array developed for grape to show the effects of ascertainment bias and to reconstruct evolutionary relationships among Vitis species. We demonstrate that phylogenies constructed using hybridization intensities suffer less from the distorting effects of ascertainment bias, and are thus more accurate than phylogenies based on genotype calls. Moreover, we reconstruct the phylogeny of the genus Vitis using hybridization data, show that North American subgenus Vitis species are monophyletic, and resolve several previously poorly known relationships among North American species. This study builds on earlier work that applied the Vitis9kSNP array to evolutionary questions within Vitis vinifera and has general implications for addressing ascertainment bias in array-enabled phylogeny reconstruction.
Data from: Development of highly reliable in silico SNP resource and genotyping assay from exome capture and sequencing: an example from black spruce (Picea mariana)
Picea mariana is a widely distributed boreal conifer across Canada and the subject of advanced breeding programs for which population genomics and genomic selection approaches are being developed. Targeted sequencing was achieved after capturing P. mariana exome with probes designed from the sequenced transcriptome of Picea glauca, a distant relative. A high capture efficiency of 75.9% was reached although spruce has a complex and large genome including gene sequences interspersed by some long introns. The results confirmed the relevance of using probes from congeneric species to perform successfully interspecific exome capture in the genus Picea. A bioinformatics pipeline was developed including stringent criteria that helped detect a set of 97 075 highly reliable in silico SNPs. These SNPs were distributed across 14 909 genes. Part of an Infinium iSelect array was used to estimate the rate of true positives by validating 4267 of the predicted in silico SNPs by genotyping trees from P. mariana populations. The true positive rate was 96.2%, for in silico SNPs compared to a genotyping success rate of 96.7% for a set 1115 P. mariana control SNPs recycled from previous genotyping arrays. These results indicate the high success rate of the genotyping array and the relevance of the selection criteria used to delineate the new P. mariana in silico SNP resource. Furthermore, in silico SNPs were generally of medium to high frequency in natural populations, thus providing high informative value for future population genomics applications.
SNP data for Syringa vulgaris genotypes
<p><span>Common lilac (<em>Syringa</em> <em>vulgaris</em> L.) is a popular landscaping plant. In the present study, its genotypes were investigated using genotyping-by-sequencing (GBS) methodology. Our aim was to obtain a large set of SNP markers, to reveal the precise identities of the investigated <em>S. vulgaris</em> accessions, and to discover genetic relationships among them. The studied plant material included local Finnish, previously unidentified accessions, known reference cultivars, and so-called historical accessions i.e., old shrubs growing in historic cultural landscapes. We intended to verify cultivar names for some valuable local common lilac accessions and to provide insights into the history of common lilac cultivation in Finland. In the analyses, we used a set of 15,007 SNP markers.</span> <span>First, polymorphic information contents (PIC) were calculated (mean 0.190, range 0.012–0.500 per marker). Then, to investigate genetic relationships among genotypes, a phylogenetic tree was constructed, and a principal coordinate analysis (PCoA) was conducted. A Bayesian analysis of population structure was carried out to determine the number and distribution of genetic clusters among samples. Genetic marker data combined with existing historical and phenotypic knowledge revealed novel information on the unidentified cultivars and on the genetic relationships among studied accessions, and solved the arrival and early history of common lilac in Finland. Overall, such comprehensive genomic characterization and deep understanding of genetic relationships of <em>S. vulgaris</em> can be used when utilizing present cultivars and developing new ones in future breeding programs.</span></p>
Data from: A 34K SNP genotyping array for Populus trichocarpa: Design, application to the study of natural populations and transferability to other Populus species
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Data from: SNP markers tightly linked to root knot nematode resistance in grapevine (Vitis cinerea) identified by a genotyping-by-sequencing approach followed by Sequenom MassARRAY validation
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Data from: Vitis phylogenomics: hybridization intensities from a SNP array outperform genotype calls
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Data from: SNP discovery in wild and domesticated populations of blue catfish, Ictalurus furcatus, using genotyping-by-sequencing and subsequent SNP validation
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Data from: More affordable and effective noninvasive SNP genotyping using high-throughput amplicon sequencing
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International Brain Laboratory public data
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OpenNeuro
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